Information processing apparatus, information processing method, information processing system and non-transitory computer readable medium

ABSTRACT

According to one embodiment, an information processing apparatus includes: a weight determiner configured to determine weights of a plurality of travel paths in a travel path network based on timings at which a first moving object travels on travel paths included in a first route among the plurality of travel paths; and a route creator configured to create a second route on which a second moving object travels in the travel path network based on the weights of the plurality of travel paths.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is based upon and claims the benefit of priority fromthe prior Japanese Patent Application No. 2020-089945, filed on May 22,2020, the entire contents of which are incorporated herein by reference.

FIELD

Embodiments described herein relate to an information processingapparatus, information processing method, information processing systemand computer program.

BACKGROUND

In a system where a plurality of moving objects travel at the same time,the efficiency of the whole system decreases due to congestion andcollision between the moving objects. A method is needed for creatingroutes that allow a plurality of moving objects to travel in anefficient way.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary configuration of an operation schedulingsystem according to a first embodiment;

FIG. 2 is a schematic diagram illustrating an exemplary travel pathnetwork;

FIG. 3 illustrates exemplary travel path structure information generatedbased on the travel path network shown in FIG. 2;

FIG. 4 illustrates a plurality of exemplary time-series networksgenerated by a time-series network generator;

FIG. 5 illustrates an example in which travel schedules for movingobjects other than a target moving object, which have been createdbefore a travel schedule is created for the target moving object, arereflected on the travel path structure information;

FIG. 6 illustrates exemplary time-series networks that show the rangesof travel by the other moving objects;

FIG. 7 illustrates an exemplary travelable networks to which informationon ranges reachable by the target moving object is set;

FIG. 8 schematically illustrates an example of obtaining the weights ofarcs in the ranges reachable by the target moving object;

FIG. 9 illustrates an exemplary route created for the target movingobject;

FIG. 10 illustrates a plurality of time-series networks generated by thetime-series network generator;

FIG. 11 illustrates an example of obtaining the weights of arcs includedin the ranges reachable by the next target moving object;

FIG. 12 illustrates an exemplary route created for the next targetmoving object;

FIG. 13 is a flow chart illustrating exemplary operations of anoperation scheduling apparatus according to the first embodiment;

FIG. 14 illustrates an exemplary configuration of an operationscheduling system according to a second embodiment;

FIG. 15 illustrates exemplary time-series networks corresponding torespective times in the initial state;

FIG. 16 illustrates a route of the target moving object created based onthe time-series networks in FIG. 15;

FIG. 17 illustrates the route of the next target moving object createdbased on the time-series networks in FIG. 15;

FIG. 18 illustrates an exemplary configuration of an operationscheduling system according to a third embodiment;

FIG. 19 illustrates an exemplary configuration of an operationscheduling system according to a fourth embodiment;

FIG. 20 illustrates an exemplary configuration of an operationscheduling system according to a fifth embodiment;

FIG. 21 is a block diagram illustrating an operation scheduling systemaccording to a sixth embodiment;

FIG. 22 is a block diagram illustrating an operation scheduling systemaccording to the second to fifth embodiments combined;

FIG. 23 is a block diagram illustrating an operation scheduling systemaccording to the second to sixth embodiments combined; and

FIG. 24 is a block diagram illustrating the hardware of an informationprocessing apparatus according to the embodiments.

DETAILED DESCRIPTION

According to one embodiment, an information processing apparatusincludes: a weight determiner configured to determine weights of aplurality of travel paths in a travel path network based on timings atwhich a first moving object travels on travel paths included in a firstroute among the plurality of travel paths; and a route creatorconfigured to create a second route on which a second moving objecttravels in the travel path network based on the weights of the pluralityof travel paths.

Below, the technological background of the embodiments will bedescribed. In recent years, manufacturing of a wide variety of productsin small quantities has become common, and accordingly productionprocesses need to be flexible. For example, respective processes of aproduction line are modularized and freely rearranged, and deliveriesbetween the processes are made using automatic guided vehicles (AGVs).For another example, mobile robots having a working arm are used, whichcan travel and work across a plurality of work sites.

Because of an acute shortage of frontline workers in logistics, more andmore labor-saving efforts are made in logistics centers for onlineshopping. This problem may be addressed, for example, by combining AGVs,self-driving forklifts and picking robots.

With the advance of the self-driving technology for automobiles,automated valet parking, in which unmanned automobiles drive and parkthemselves in a parking space, has reached a practical level. Techniquesto drive unmanned construction machine moving objects by remote controlin a construction site or mining site have also reached a practicallevel.

For autonomous moving objects that identify their own positions whilethey are traveling, it is difficult to manage their travel strictlybased on traveling time and therefore the moving objects mayunexpectedly travel in opposite directions somewhere on a free plane.This may cause deadlock depending on the structure of travel paths.

In order to efficiently control travel of many self-driving movingobjects in a narrow area, it is necessary to prevent contention such ascollision and deadlock between the moving objects. This isconventionally addressed by providing double-track travel paths thatallow moving objects to travel simultaneously in opposite directions, aplurality of unidirectional loops, or dedicated grid-like travel pathsor traveling spaces.

Given the use of such dedicated travel paths, in one related art,schedules are made so that any moving objects will not travel inopposite directions on any routes of the moving objects. In a case whereexisting paths for human workers are diverted in stages to self-drivingmoving objects, however, it could be inevitable to use travel pathshaving an arrangement that can cause travel in opposite directions onthe same travel path, or for safety reasons, it could be inevitable tospecify travel paths that can cause travel in opposite directions. Thus,a versatile system is needed, which can make operation schedules even insuch cases. The aforementioned related art cannot be applied in theseconditions.

In another related art, a travel schedule is made for each moving object(each moving object is reserved) in turn. A travel schedule for a movingobject is made so that the moving object and any of the previouslyreserved moving objects will not travel in opposite directions. Aproblem with this related art is that the efficiency of travel of movingobjects varies significantly depending on the order of reservations ofthe moving objects, which results in a decrease in the efficiency of thewhole system.

The use of dedicated travel paths requires extra construction costs andmakes it difficult to change the layout of the travel paths in stagesafter the start of operation.

One of the techniques to solve this problem is to predict an occurrenceof contention such as collision and deadlock between moving objects, andif contention is predicted to occur, create schedules such that one ofthe contending moving objects is kept waiting to prevent the contention.In this technique, a plurality of moving objects may be kept waitingbefore the same node (intersection of travel paths) for a long time,which again leads to a decrease in the efficiency of the whole system.

Another technique to solve the problem is to indicate where each movingobject is in each time range by way of a network called “time-seriesnetwork”, and create travel schedules such that multiple moving objectscannot be at the same place in the same time range. In this technique,the route of each moving object is optimized by dividing the scheduleperiod into multiple time ranges having the same length and calculatingthe states of all moving objects in each time range. Consequently, thesize of a travel path network, the length of a schedule period and thegranularity of time ranges are limited for practical use. In addition,if travel schedules for a plurality of moving objects are created onlyfor a short period of time from the start of the schedule period, theschedules may cause the moving objects to be concentrated and stuck in aportion of a network.

The embodiments of the present invention enable efficient travel of aplurality of moving objects such as AGVs and mobile robots by preventingcontention such as collision and deadlock between the moving objectswhen the moving objects travel at the same time. A moving objectaccording to the embodiments may be an autonomous moving object thatidentify its own position while it is traveling on a free plane, or anon-autonomous moving object that travels on dedicated travel paths suchas laid rails or guide tapes. The embodiments will be described indetail below.

The embodiments will be described with reference to the accompanyingdrawings.

First Embodiment

FIG. 1 illustrates an exemplary configuration of an operation schedulingsystem according to a first embodiment. The operation scheduling system1 in FIG. 1 includes an operation scheduling apparatus 10, which is aninformation processing apparatus, and an operation management apparatus200. The operation scheduling apparatus 10 creates travel schedules formoving objects 303_1-303N and manages travel of the moving objects303_1-303N based on the created travel schedules. The moving objects303_1-303N may be automatically travelable moving objects such asautomatic guided vehicles (AGVs), autonomous mobile robots andself-driving vehicles (e.g., self-driving cars). Any of the movingobjects 303_1-303N is hereinafter referred to as a moving object 303.

The moving objects 303 travels in a travel path network including aplurality of travel paths on which the moving objects can travel. Thetravel path network is composed of a plurality of travel paths that areconnected to each other. A connection point of travel paths representsan intersection of travel paths where a moving object can change travelpaths. An end of a travel path which is not connected to an intersectionis a dead end. A specific example of the travel path network will bedescribed below with reference to FIG. 2. The travel path network isdeployed, for example, in a plant, warehouse or facility premises. Themoving objects 303 may have a battery and travel and operate on electricpower stored in the battery. The moving objects can travel forward andmay also be able to travel backward. The moving objects may travel bysteering control or may be rotatable to reverse its direction. Themoving objects may travel in a direction other than the forward andbackward directions, for example, a diagonal direction.

The travel path network includes sensors 401_1-401_M that detect thestates of the moving objects 303 and communication devices 501_1-501Kthat can communicate with the moving objects 303. Any of the sensors401_1-401_M is hereinafter referred to as a sensor 401. Any of thecommunication devices 501_1-501K is hereinafter referred to as acommunication device 501. The sensors 401 and the communication devices501 are located along travel paths, at ends of travel paths, at pointswhere travel paths cross (intersections), or any other points in thetravel path network.

FIG. 2 is a schematic diagram illustrating an exemplary travel pathnetwork. In FIG. 2, a circle represents a point where travel paths cross(intersection) or an end of a travel path, and the number in the circleis the identifier of the intersection or the end. A line connectingcircles represents a travel path between two intersections, on whichmoving objects can travel. Moving objects are traveling in a directionof arrow between intersections 6 and 7, between intersections 4 and 10and between intersections 25 and 26, respectively.

In the example in FIG. 2, each travel path is straight but it may becurved or include both a straight portion and a curved portion. Thetravel paths may be built with guide tapes. Markers may be deployed atkey points on the travel paths for the moving objects to determine whichtravel paths they take, or the moving objects may detect their ownpositions and identify virtual travel paths.

The number of moving objects that can travel on a travel path (i.e., thenumber of lanes) may be predetermined. For example, if the number ofmoving objects is one, two moving objects cannot travel in oppositedirections at the same time (i.e., cannot pass each other) on the travelpath, or a moving object cannot overtake another moving object on thetravel path when those moving objects are traveling in the samedirection. If the number of moving objects is two, two moving objectscan travel in opposite directions at the same time (i.e., can pass eachother) on the travel path, or a moving object can overtake anothermoving object on the travel path. Although the present embodiment isdescribed in reference to travel paths on which two moving objectscannot pass each other or a moving object cannot overtake another movingobject, the present embodiment can be applied to any types of travelpaths. When two moving objects travel in opposite directions or collidewith each other on such a travel path, contention occurs. If the movingobjects is travelable both forward and backward or rotatable to changetheir directions, contention can be solved by one of the two movingobjects traveling back along the same travel path. If both the twomoving objects is travelable only in the forward direction and is notrotatable, contention cannot be solved. Even when contention issolvable, solving contention is time-consuming. Thus, it is desirablethat a travel schedule for each moving object causes as littlecontention as possible.

A graph representation of a travel path network such as that depicted inFIG. 2 is referred to as travel path structure information. Travel pathstructure information can be generated by generating nodes correspondingto intersections or ends, arcs corresponding to travel paths betweenintersections and between intersections and ends, and connecting thenodes by the arcs.

FIG. 3 illustrates exemplary travel path structure information generatedbased on the travel path network shown in FIG. 2. A circle represents anode and the number in the circle is the identifier of the node.Although the identifier of a node is the same as the identifier of theintersection corresponding to the node, those identifiers may bedifferent as long as the correspondence between them can be determined.

A node has node information including a node ID, an x-coordinate, ay-coordinate and a node type (intersection, end, etc.). An arc has arcinformation including the node ID of one of the two nodes at both endsof the arc and the node ID of the other node.

A travel path structure storage 11 stores travel path structureinformation generated based on the travel path network. The travel pathstructure information may include the coordinates of a plurality ofnodes and a plurality of arcs connecting the plurality of nodes, forexample.

An operation schedule storage 12 stores operation schedules includingpoints of departure and points of arrival for a plurality of movingobjects. The operation schedule storage 12 may store times of departureand points through which moving objects have to travel. If movingobjects have tasks to be performed on the way to their points ofarrival, the operation schedule storage 12 may also store information onwhat the moving objects have to do for the tasks and where the movingobjects have to perform the tasks.

A state storage 13 stores the state of each moving object. The state ofa moving object includes whether the moving object is carrying loads ornot, the position, velocity, traveling direction on a travel path andremaining battery power of the moving object. The state of a movingobject may also include information on specifications such as thestandard velocity, maximum velocity, minimum velocity, size, travelabledirections of the moving object. The state of a moving object may beobtained by a communicator 201 of the operation management apparatus 200communicating with the moving object, or by a state detector 202 of theoperation management apparatus 200 from the moving object via at leastone of the sensors 401 and the communication devices 501. When themoving object is out of the communication range of the communicator 201,the moving object notifies its state to the operation schedulingapparatus 10 via the sensors 401 or the communication devices 501located along travel paths or at intersections.

A travel schedule storage 16 stores a travel schedule for each movingobject created by a route scheduler 100 that is described below. Thetravel schedule includes the point of departure and the point of arrivalof the moving object, points through which the moving object has totravel and a timing at which the moving object travels through each ofthose points (at least one of the arrival time, departure time andpassage time). The route scheduler 100 creates a travel schedule foreach moving object by first creating a route for the moving object andthen determining a timing at which the moving object travels througheach node (point) included in the route (at least one of the arrivaltime, departure time and passage time). One of the features of thepresent embodiment consists in a process of creating a route for eachmoving object by the route scheduler 100.

Based on the travel schedule for each moving object, a director 14generates an instruction that instructs the moving object to travelaccording to the travel schedule. For example, the director 14 maygenerate an instruction that instructs each moving object to travelaccording to the travel schedule for the moving object. The director 14provides the generated instruction to a communicator 15. For example,the instruction may include a sequence of commands that instruct themoving object to travel on travel paths (arcs) indicated by the travelschedule in sequence, but the instruction may be in any format. Theinstruction may include a command that specifies a traveling velocity ontravel paths, or a command that specifies a task to be performed (e.g.,putting loads on shelves located along travel paths or picking up loadsfrom shelves). If the moving object is not at the point of departurebefore execution of the travel schedule, the director 14 may generate aninstruction that instructs the moving object to move to the point ofdeparture. The director 14 may generate an instruction that instructeach moving object to return the state of the moving object.

The communicator 15 is in wired or wireless communication with theoperation management apparatus 200. The operation management apparatus200 and the operation scheduling apparatus 10 may be included in thesame apparatus. In this case, the communicator 15 may be integrated withthe communicator 201 of the operation management apparatus 200. Thecommunicator 15 transmits an instruction for a moving object to thecommunicator 201 of the operation management apparatus 200. Thecommunicator 201 transmits the instruction for the moving object to themoving object by wired or wireless communication. The moving objecttravels according to the instruction received from the communicator 201.If contention occurs between the moving object and another movingobject, the moving object may autonomously perform operations to solvethe contention. For example, if two moving objects travel simultaneouslyin opposite directions on a travel path that do not allow such travel,one of the two moving objects may travel back along the same travel pathand wait at the side of the entrance of the travel path.

The state detector 202 of the operation management apparatus 200 obtainsinformation indicating the state of a moving object via at least one ofthe sensors 401 and the communication devices 501. The communicator 201transmits the information indicating the state obtained by the statedetector 202 to the communicator 15. The communicator 15 stores thereceived information indicating the state in the state storage 13. Forexample, the state of the moving object may be stored in the statestorage 13, with the ID of the moving object and a timestamp associatedwith the state of the moving object.

The route scheduler 100 creates routes on which a plurality of movingobjects travel. The route scheduler 100 creates a travel schedule foreach of the moving objects by determining a timing at which the movingobject travels through each node (point) included in the created routeof the moving object (at least one of the arrival time, departure timeand passage time). If the operation schedules of the moving objectsinclude tasks to be performed by the moving objects, the tasks andtimings of performing the tasks may be added to the travel schedules. Ifthe operation schedules include tasks that can be performed by anymoving objects, the tasks may be assigned to moving objects that arriveearliest at locations where the tasks are to be carried out.

The route scheduler 100 includes a time-series network generator 101, atravelable network generator 102, a route creator 103 and a weightdeterminer 104.

The time-series network generator 101 divides a period of time for whichtravel schedules are created into a plurality of times (time ranges) andgenerates a plurality of time-series networks corresponding to theplurality of times respectively based on the travel path structureinformation. The time-series networks corresponding to the respectivetimes are generated, for example, by copying the travel path structureinformation. If the travel path structure does not change during theperiod for which travel schedules are created (in the presentembodiment, this is assumed to be true), the time-series networkscorresponding to the respective times respectively are the same. Thegenerated time-series networks are in the initial state.

FIG. 4 illustrates a plurality of exemplary time-series networksgenerated by the time-series network generator 101. In this example,time-series networks are shown, which are generated for the respectivetimes (from 0 to 1 second, from 1 to 3 seconds, from 3 to 10 seconds andfrom 10 to 60 seconds) in a case where a travel schedule is created fora certain moving object (target moving object) for 60 seconds from theschedule start time.

The time lengths of the generated time-series networks vary (i.e.,uneven) and become longer over time. The time lengths of the time-seriesnetworks may be specified by a user. A user may specify a time ofparticular interest and then finely adjust the length(s) of a time rangeor ranges after, before, or around the time. The time lengths of thetime-series networks may be the same. In the example in FIG. 4, the timelengths of the time-series networks become longer over time to reducethe total number of time-series networks and thereby reducecomputational complexity.

In FIG. 5, travel schedules for moving objects A, B and C, which havebeen created before the travel schedule for the target moving object iscreated, are reflected (represented as graphs) on the travel pathstructure information. The route of each moving object and the arrivaltime (or passage time) at each node included in the route are shown.Although the start times of the schedules are the same for all themoving objects, the departure times of the moving objects from theirpoints of departure do not need to be the same as the start times of theschedules. The travel schedules for the moving objects A, B and C havebeen created by the route scheduler 100 before the travel schedule forthe target moving object is created. The travel schedules for the movingobjects A, B and C may be created in a manner different from thatdescribed in the present embodiment (e.g., the travel schedules may beuser-created).

In FIG. 5, the point of departure of the route for the moving object Ais node 2 and the point of arrival is node 28. Similarly, the point ofdeparture of the route for the moving object B is node 27 and the pointof arrival is node 1. The point of departure of the route for the movingobject C is node 10 and the point of arrival is node 9.

Suppose that moving objects D and E are target moving objects for whichtravel schedules are to be created next. The operation schedulespecifies that the point of departure of the moving object D is node 8and the point of arrival is node 21, but the route of the moving objectD has not been determined. The operation schedule specifies that thepoint of departure of the moving object E is node 11 and the point ofarrival is node 9, but the route of the moving object E has not beendetermined.

The travelable network generator 102 reflects the travel schedules ofthe moving objects A, B and C (see FIG. 5) on the time-series networkscorresponding to the respective times (see FIG. 4). The time-seriesnetworks corresponding to the respective times on which the travelschedules of the moving objects A, B and C (first moving objects) arereflected constitute first information including travel paths on whichthe first moving objects travel for the plurality of times.

First, arcs are calculated, on which the moving objects A-C are totravel (exist) from 0 (the start time of the travel schedules) to 1second. The moving object A is to travel on arc (2, 3), the movingobject B is to travel on arc (27, 26), and the moving object C is totravel on arc (10, 11). Information indicating the calculated arcs isset to the time-series network corresponding to the time from 0 to 1second.

The leftmost graph in FIG. 6 illustrates an example in which informationindicating arcs on which the moving objects A, B and C are to travelfrom 0 to 1 second is set to the time-series network corresponding tothe time from 0 to 1 second.

The second graph from left in FIG. 6 illustrates an example in whichinformation indicating arcs on which the moving objects A, B and C areto travel from 1 to 3 seconds is set to the time-series networkcorresponding to the time from 1 to 3 seconds.

The third graph from left in FIG. 6 illustrates an example in whichinformation indicating arcs on which the moving objects A, B and C areto travel from 3 to 10 seconds is set to the time-series networkcorresponding to the time from 3 to 10 seconds.

The rightmost graph in FIG. 6 illustrates an example in whichinformation indicating arcs on which the moving objects A, B and C areto travel from 10 to 60 seconds is set to the time-series networkcorresponding to the time from 10 to 60 seconds.

The travelable network generator 102 calculates ranges which the targetmoving object can reach (in which the target moving object can exist) inthe time-series networks corresponding to the respective times in 60seconds. In doing so, it is assumed that the target moving objecttravels at a velocity that is determined in a predetermined manner. Forexample, the velocity of the moving object may be assumed to beconstant, or the velocity may be adjusted depending on the inclinationof travel paths or the presence or absence of loads. The travelablenetwork generator 102 sets information indicating the ranges which thetarget moving object can reach (in which the target moving object canexists), more specifically, information indicating arcs included inthose ranges, to the time-series networks corresponding to therespective times. The time-series networks to which informationindicating the ranges is set are referred to as travelable networks forthe target moving object. The travelable networks corresponding to theplurality of times constitute first information including travel pathswhich the target moving object can reach in the plurality of times.

This will be described in more detail on the assumption that the movingobject D is the target moving object. A range in each time-seriesnetwork which the moving object D can start from the node 8 and reach(in which the moving object D can exist) within 60 seconds iscalculated.

In the time-series network corresponding to the time from 0 to 1 second,the moving object D can be at node 8 or on one of the four arcsconnected to node 8. Information indicating the four arcs is, therefore,set to the time-series network corresponding to the time from 0 to 1second. As a specific example of this calculation, Dijkstra's algorithmmay be used to calculate the distance from the departure node to eachnode in the travel path network. Then, nodes which the moving object Dcan reach from 0 to 1 second are determined. Arcs to the determinednodes are regarded as reachable arcs of the moving object D.

The leftmost graph in FIG. 7 illustrates an exemplary travelable networkin which information on a range where the moving object D can exist isset to the time-series network corresponding to the time from 0 to 1second.

Next, in the time-series network corresponding to the time from 1 to 3seconds, a range (range 2) is determined, in which the moving object Dcan move from the four arcs connected to node 8 in 2 seconds (from 1 to3 seconds), in addition to the range (range 1) in which the movingobject D can exist from 0 to 1 second. The moving object D can exist onarcs in the range 1 or range 2. As a specific example of thiscalculation, nodes which the moving object D can reach from thedeparture node from 0 to 3 seconds may be determined based on thedistance to each node. Arcs to the determined nodes are regarded asreachable arcs of the moving object D.

The second graph from left in FIG. 7 illustrates an exemplary travelablenetwork in which information on a range where the moving object D canexist is set to the time-series network corresponding to the time from 1to 3 seconds.

In a similar manner, arcs on which the moving object D can exist aredetermined in the time-series network corresponding to the time from 3to 10 seconds. As a specific example of this calculation, nodes whichthe moving object D can reach from the departure node from 0 to 10seconds may be determined based on the distance to each node. Arcs tothe determined nodes are regarded as reachable arcs for the movingobject D.

The third graph from left in FIG. 7 illustrates an exemplary travelablenetwork in which information on a range where the moving object D canexist is set to the time-series network corresponding to the time from 3to 10 seconds.

Similarly, arcs on which the moving object D can exist are determined inthe time-series network corresponding to the time from 10 to 60 seconds.As a specific example of this calculation, nodes which the moving objectD can reach from the departure node from 0 to 60 seconds may bedetermined based on the distance to each node. Arcs to the determinednodes are regarded as reachable arcs for the moving object D.

The rightmost graph in FIG. 7 illustrates an exemplary travelablenetwork in which information on a range where the moving object D canexist is set to the time-series network corresponding to the time from10 to 60 seconds.

The route creator 103 creates a route for the target moving object baseon the travelable networks corresponding to the respective times (firstinformation including travel paths which the moving object can reach inthe plurality of times) and the weights of travel paths in the travelpath network corresponding to the respective times.

In particular, the route creator 103 obtains the weights of arcsincluded in ranges which the target moving object can reach (alsoreferred to as first arcs) in the travelable networks corresponding tothe respective times. The weights of the first arcs are preset in thetime-series networks corresponding to the respective times. Morespecifically, the weights of arcs in the time-series networkscorresponding to the respective times are determined (or updated) by theweight determiner 104 when routes are created for the moving objectsA-C. For example, sufficiently large values are given to arcs includedin the route of at least one of the moving objects A-C, and the minimumvalue (e.g., zero) is given to arcs that are not included in any routesof the moving objects A-C. If the routes of the moving objects A-C aredetermined differently from using the operation scheduling system, theweights of arcs may be set in any suitable manner.

FIG. 8 schematically illustrates an example of obtaining the weights ofarcs included in the ranges which the target moving object can reach(first arcs) in the travelable networks corresponding to the respectivetimes. Arrows (indicating the routes of the moving objects A-C) aredrawn along first arcs that are included in the routes of the movingobjects A-C. The first arcs included in the route of at least one of themoving objects A-C have weights larger than the minimum value. Firstarcs that are not included in any routes of the moving objects A-C havethe minimum weight. The travelable networks corresponding to therespective times in which the first arcs are associated with theobtained weights are referred to as “weighted travelable networks.”

The leftmost graph in FIG. 8 illustrates the weighted travelable networkcorresponding to the time from 0 to 1 second. No first arc is includedin the routes of the moving objects A-C and all the first arcs have theminimum weight.

The second graph from left in FIG. 8 illustrates the weighted travelablenetwork corresponding to the time from 1 to 3 seconds. No first arc isincluded in the routes of the moving objects A-C and all the first arcshave the minimum weight.

The third graph from left in FIG. 8 illustrates the weighted travelablenetwork corresponding to the time from 3 to 10 seconds. Some of thefirst arcs are included in the routes of the moving objects A-C andtherefore have sufficiently large weights. All the other first arcs havethe minimum weight.

The rightmost graph in FIG. 8 illustrates the weighted travelablenetwork corresponding to the time from 10 to 60 seconds. Some of thefirst arcs are included in the routes of the moving objects A-C andtherefore have sufficiently large weights. All the other first arcs havethe minimum weight.

As can be seen from FIG. 8, the weights of the first arcs changeaccording to time. For example, in the third graph from left in FIG. 8,arc (3, 4) has a sufficiently large weight, but in the fourth graph fromleft in FIG. 8, arc (3, 4) has the minimum weight.

The route creator 103 creates a route from the departure node to thearrival node for the target moving object based on the weightedtravelable networks corresponding to the respective times. For example,the route creator 103 may search for the shortest weighted route byDijkstra's algorithm. In this case, normalized weights are calculated bydividing the weights of the first arcs by the lengths of the travelpaths corresponding to the first arcs respectively. The route creator103 searches for a set of arcs (travel paths) from the departure node tothe arrival node, the sum of the normalized weights of which is thesmallest or smaller than a threshold. The route from the departure nodeto the arrival node via the found nodes and arcs between them isselected as a route for the target moving object. In this example, theweights of the first arcs are divided by the lengths but this may beomitted if the weights are reflective of the lengths. It is assumed thatthe target moving object travels at a velocity that is determined in apredetermined manner. The velocity of the moving object may be assumedto be constant, or the velocity may be adjusted depending on theinclination of travel paths or the presence or absence of loads. Atiming (the departure time, passage time or arrival time) is calculated,at which the target moving object travels through each node included inits route if the moving object travels at the determined velocity. Atravel schedule is created by adding the timing at which the targetmoving object travels through each node to the route of the targetmoving object. The created travel schedule for the target moving objectis stored in the travel schedule storage 16.

FIG. 9 illustrates an exemplary route created for the target movingobject (at this point, the moving object D) by the route creator 103. Inthe travelable networks corresponding to the respective times, the routecreated for the target moving object is indicated by “D.”

The weight determiner 104 sets the weight of each arc included in theroute created for the moving object D for the respective times. Forexample, the weight determiner 104 assigns, as a weight to arcs includedin the route of the moving object D, a fixed value sufficiently largerthan the maximum value of an objective function (e.g., the objectivefunction of Dijkstra's algorithm). If an arc included in the route ofthe moving object D is also included in a route previously calculatedfor another moving object, the weight of the arc already has a largevalue and therefore may not be changed. In this way, the weightdeterminer 104 determines the weights of a plurality of travel paths inthe travel path network based on timings at which the moving object Dtravels on travel paths (arcs) included in the route of the movingobject D. In other words, the weight determiner 104 determines, based ontimings at which the moving object D travels on travel paths, theweights of the plurality of travel paths for selecting travel paths onwhich the next target moving object, i.e., the moving object E, is totravel when a route for the moving object E is subsequently created.

As it is closer to the schedule start time (0 seconds), larger weightsmay be assigned to arcs. The weights of the arcs may be decreased overtime. For example, if the moving object D is likely to travel on thetravel path corresponding to a certain arc at the earliest time, the arcmay be assigned a value sufficiently larger than the maximum value ofthe objective function to reduce the possibility of contention with theother moving objects. As time advances, however, the operation of themoving object D may be deviating from its travel schedule (e.g., anobstacle on a travel path causes delay of travel), or additional tasksmay be assigned to the moving object D. Accordingly, as time passes, themoving object D is less likely to travel on the travel path, andtherefore the weight of the arc may be decreased. Consequently, theweight may fall below the maximum value of the objective function.

In this manner, by increasing the weights of arcs at the earliest timeand decreasing them over time, it is possible to reduce contention thatis highly likely to happen at the earliest time rather than makingelaborate schedules for the distant future.

In the example described above, the weights of arcs included in theroute created for the moving object D are set. Before that, the weightsof arcs included in the routes of the moving objects A-C are set in asimilar manner when the routes are created for the moving objects A-C.With an increase in the number of moving objects that move on the samearc at the same time, the weight of the arc may be increased. The weightof a travel path may be set to a value sufficiently larger than themaximum value of the objective function regardless of the number ofmoving objects that travel on the travel path as long as at least onemoving object travels on the travel path (this is the case with theaforementioned example).

FIGS. 10-12 illustrate exemplary data output from the time-seriesnetwork generator 101, the travelable network generator 102 and theroute creator 103 when a route for the moving object E is createdsubsequent to the creation of the route of the moving object D.

FIG. 10 illustrates an example in which information indicating arcs onwhich the moving objects A-D are to travel is set to the time-seriesnetworks corresponding to the respective times created by thetime-series network generator 101.

The leftmost graph in FIG. 10 illustrates an example in whichinformation indicating arcs on which the moving objects A-D are totravel from 0 to 1 second is set to the time-series networkcorresponding to the time from 0 to 1 second (note that the movingobject D is at its departure node).

The second graph from left in FIG. 10 illustrates an example in whichinformation indicating arcs on which the moving objects A-D are totravel from 1 to 3 seconds is set to the time-series networkcorresponding to the time from 1 to 3 seconds.

The third graph from left in FIG. 10 illustrates an example in whichinformation indicating arcs on which the moving objects A-D are totravel from 3 to 10 seconds is set to the time-series networkcorresponding to the time from 3 to 10 seconds.

The rightmost graph in FIG. 10 illustrates an example in whichinformation indicating arcs on which the moving objects A-D are totravel from 10 to 60 seconds is set to the time-series networkcorresponding to the time from 10 to 60 seconds.

FIG. 11 illustrates exemplary weighted travelable networks correspondingto the respective times for the moving object E. In particular, in FIG.11, ranges which the moving object E can reach (in which the movingobject E can exist) are set in the travelable networks corresponding tothe respective times. Weights for arcs included in the ranges (firstarcs) are determined and associated with the first arcs (the values ofthe weights are not shown). Arrows are drawn along first arcs includedin the route of at least one of the moving objects A-D to indicate theroute. The first arcs included in the route of at least one of themoving objects A-D have sufficiently large weights. First arcs that arenot included in any routes of the moving objects A-D have the minimumweight. The leftmost graph in FIG. 11 illustrates the weightedtravelable network corresponding to the time from 0 to 1 second. Thesecond graph from left in FIG. 11 illustrates the weighted travelablenetwork corresponding to the time from 1 to 3 seconds. The third graphfrom left in FIG. 11 illustrates the weighted travelable networkcorresponding to the time from 3 to 10 seconds. The rightmost graph inFIG. 11 illustrates the weighted travelable network corresponding to thetime from 10 to 60 seconds.

FIG. 12 illustrates an exemplary route created for the target movingobject (at this point, the moving object E) by the route creator 103.The route on which the target moving object E travels is indicated inthe travelable networks corresponding to the respective times. The routeon which the moving object E travels is indicated by “E.”

In the example described above, routes are created for the movingobjects D and E. Before that, routes for the moving objects A, B and Care created in this order. An additional description is given of how tocreate a route for the first target moving object, i.e., the movingobject A. When a route is created for the moving object A first, in thetravel path structure information, the weights of arcs may be set bydefault to values that depend on the lengths of the travel pathscorresponding to the arcs. The shortest route from the point ofdeparture to the point of arrival is determined by searching for a routewhich has the minimum or quasi-minimum total weight and selected as theroute of the moving object A. The weights of the arcs corresponding totravel paths included in the route of the moving object A are set. Thesetting may be carried out in a manner similar to that used to determineweights in the above examples. As a result, the weights of the arcsincluded in the route of the moving object A are set to valuessufficiently larger than the maximum value of the objective function.The weights may be decreased over time. The weights of arcs that are notincluded in the route of the moving object A may be unchanged from thedefault values or set to the minimum value (although, in the aboveexamples, the weights of arcs that are not included in the routes of themoving objects are set to the minimum value, the default values may beused instead of the minimum value if it is desirable to keep the defaultvalues). After the route of the moving object A and the weights of thearcs included in the route are set, routes for the moving objects B andC are created in sequence in a manner similar to that described above.

FIG. 13 is a flow chart illustrating exemplary operations of theoperation scheduling apparatus 10 according to the present embodiment.

In step S101, the time-series network generator 101 divides a period oftime for which travel schedules are created into a plurality of timesand generates a plurality of time-series networks corresponding to theplurality of times respectively based on travel path structureinformation. In the initial state, the time-series networkscorresponding to the respective times are the same. The time lengths ofthe generated time-series networks may vary (or uneven).

In step S102, the travelable network generator 102 selects one movingobject as the target moving object from a plurality of moving objectsfor which schedules are created (S102).

In step S103, the travelable network generator 102 reflects travelschedules previously created for other moving objects on the time-seriesnetworks corresponding to the respective times. The travelable networkgenerator 102 calculates ranges which the target moving object can reach(in which the target moving object can exist) in the time-seriesnetworks corresponding to the respective times. Information indicatingthe ranges which the target moving object can reach, more particularly,information indicating arcs included in the ranges is set to thetime-series networks corresponding to the respective times. Thetime-series networks to which information indicating the ranges is setrepresent travelable networks for the target moving object.

In step S104, the route creator 103 creates a route for the targetmoving object based on the weights of the arcs in the ranges which thetarget moving object can reach (also referred to as first arcs) in thetravelable networks corresponding to the respective times.

In step S105, the weight determiner 104 updates the weights of arcsincluded in the route created for the target moving object. For example,the weight determiner 104 assigns, as a weight to the arcs included inthe route of the moving object D, a fixed numerical value sufficientlylarger than the maximum value of an objective function (e.g., theobjective function of Dijkstra's algorithm). If another moving object,for which a route has been calculated, travels an arc included in theroute of the moving object, the weight of the arc already has a largevalue.

Another moving object is selected as the next target moving object andsteps S102-S105 are repeated.

In this way, according to the present embodiment, routes for a pluralityof moving objects can be created with low computational complexity,which can reduce contention between the moving objects.

(Variation)

In the first embodiment, the point of departure and the point of arrivalare given in an operation schedule for the target moving object.Additionally, waypoints may be given. Suppose that a waypoint 1 and awaypoint 2 are given to the target moving object as well as the point ofdeparture and the point of arrival. In this case, first, a route fromthe point of departure to the waypoint 1 is calculated, then, a routefrom the waypoint 1 to the waypoint 2 is calculated, and finally, aroute from the waypoint 2 to the point of arrival is calculated. Moregenerally, a route from the point of departure to the point of arrivalvia waypoints 1−N (N is an integer equal to or more than 1) can becalculated in a similar manner.

Second Embodiment

In a second embodiment, the structure of the travel path network ischanged according to time during the schedule period. For example, thetravel path network may be changed, for example, because a load isplaced on a travel path, someone enters a travel path, the gate of atravel path is closed, new travel paths are added, or travel paths areremoved 15 seconds after the start of the schedule period. Even in suchcases, according to the present embodiment, routes and travel schedulescan be created, which allow moving objects to travel in an efficientway.

FIG. 14 illustrates an exemplary configuration of an operationscheduling system according to the second embodiment. The operationscheduling system includes a travel path alteration information inputdevice 17 in addition to the same components as those of the operationscheduling system in FIG. 1. The travel path alteration informationinput device 17 receives, as input, information that represents astructure of the travel path network (travel path structure information)and a period in which the structure of the travel path network is used(use period). The travel path alteration information input device 17 mayobtain information provided by a user, i.e., an administrator oroperator of the system, operating the system, or may receive informationfrom an external device via wired or wireless communication.

Based on the information input from the travel path alterationinformation input device 17, a travel path structure storage 11 stores aplurality of use periods in association with a plurality of pieces oftravel path structure information.

A route scheduler 100 switches the plurality of pieces of travel pathstructure information so that a piece of travel path structureinformation will be used, the use time of which conforms to the elapsedtime from the schedule start time (i.e., the route scheduler 100switches travel path networks, based on which weights are calculated forthe target moving object). A time-series network generator 101 of theroute scheduler 100 generates time-series networks corresponding torespective times in the initial state based on the pieces of travel pathstructure information according to the use period. The rest of theconfiguration and operations of the route scheduler 100 are the same asthose of the route scheduler 100 in the first embodiment.

FIG. 15 illustrates exemplary time-series networks corresponding to therespective times in the initial state. The time-series networks for thetime period from the schedule start time to 15 seconds are the same asthose in the first embodiment but the time-series network for the timeperiod from 15 to 60 seconds is different. That is, a travel pathstructure storage 11 stores two pieces of travel path structureinformation representing two travel path networks: a piece of travelpath structure information representing a travel path network for thetime period from the schedule start time to 15 seconds; and a piece oftravel path structure information representing a travel path network forthe time period from 15 to 60 seconds. At 15 seconds, the travel pathnetworks are switched and accordingly the pieces of travel pathstructure information are switched. Thus, a new time-series network isgenerated in the initial state.

In particular, as compared to the time-series network in the initialstate for the time period from 10 to 15 seconds, in the time-seriesnetwork in the initial state for the time period from 15 to 60 seconds,arcs (23, 24), (24, 25) and (25, 26) are removed.

FIG. 16 illustrates the route of the moving object D created in a mannersimilar to that in the first embodiment based on the time-seriesnetworks in the initial state in FIG. 15. The routes and the travelschedules of the moving objects A-C are created before the route of themoving object D is created. The moving object D is at node 8 from 0 to10 seconds, travels on arc (9, 16) from 10 to 15 seconds, and travels onarcs (16, 17), (17, 18), (18, 19), (19, 20) and (20, 21) from 15 to 60seconds. A travel schedule for the moving object D is created byassociating the nodes included in the route of the moving object D withthe times.

FIG. 17 illustrates the route of the moving object E created in a mannersimilar to that in the first embodiment based on the time-seriesnetworks in the initial state in FIG. 15. The route and the travelschedule of the moving object D in FIG. 16 is created before the routeof the moving object E is created.

As shown in FIGS. 16 and 17, the created routes do not pass through arcs(23, 24), (24, 25) and (25, 26) in the time period from 15 to 60seconds.

The schedule period may be divided more finely around 15 seconds. Forexample, a time-series network for the time period from 14 to 15seconds, a time-series network for the time period from 15 to 16 secondsand a time-series network for the time period from 16 to 60 seconds maybe generated. This makes it possible to create a route that can reducecontention between moving objects more certainly around the time whenthe travel path networks are switched.

In the present embodiment, a plurality of pieces of travel pathstructure information are switched according to time. Alternatively, aweight determiner 104 may change the weights of travel paths included inchanged portions of the travel path network according to time. Travelpaths that become unavailable according to time are given sufficientlylarge weights and travel paths that become available according to timeare given the minimum weight. This can achieve similar effects to thoseobtained by switching a plurality of pieces of travel path structureinformation.

According to the present embodiment, routes can be created, which allowmoving objects to travel in an efficient way even if the structure ofthe travel path network changes over time.

Third Embodiment

FIG. 18 illustrates an exemplary configuration of an operationscheduling system according to a third embodiment. The operationscheduling system includes a travel path information output device 18(first output device) in addition to the same components as those of theoperation scheduling system in FIG. 14. The travel path informationoutput device 18 outputs information including the structure of thetravel path network according to time if the structure of the travelpath network is changed according to time as in the second embodiment.In particular, the travel path information output device 18 outputsinformation including time-series networks corresponding to respectivetimes in the initial state (such as the time-series networkscorresponding to the respective times in the initial state in FIG. 15)created by a time-series network generator 101.

The output may be provided in a visible form that can be displayed onthe screen of a display device viewable to users or workers. The displaydevice may be installed on a wall in the field to be viewed by a largenumber of users simultaneously. The output information may betransmitted to an external device such as user's terminal via wired orwireless communication.

By displaying the time-series networks corresponding to the respectivetimes in the initial state on a display device, users can easilyunderstand how the travel path network changes. This makes it possible,for example, for users to prevent any moving object but the schedulingtarget moving object from using a travel path around the time when thetravel path is unavailable if the moving object uses the travel path.This also makes it possible for users prevent anyone from walking on atravel path around the time when the travel path is unavailable. Amoving object other than the scheduling target moving object may use atravel path, for example, when a worker gets on and manually drives themoving object or when a worker manipulates the moving object by remotecontrol.

Fourth Embodiment

FIG. 19 illustrates an exemplary configuration of an operationscheduling system according to a fourth embodiment. The operationscheduling system includes a reservation information input device 19 inaddition to the same components as those of the operation schedulingsystem in FIG. 1. The reservation information input device 19 receives,as input, reservation information including information identifying atravel path and a use period in which a moving object other than thescheduling target moving object uses the travel path. The use period maybe represented by a set of a start time and an end time or a set of astart time and a time length. A weight determiner 104 may set the weightof the travel path (arc) at the time reserved in the reservationinformation to a sufficiently large value. That is, the reserved travelpath at the reserved time is given a sufficiently large weight becausethe arc is used by the moving object other than the scheduling targetmoving object. A moving object other than the scheduling target movingobject may use a travel path as described in the third embodiment. Theweight of the reserved arc may be determined in a manner similar to thatused to set the weights of arcs in the first embodiment.

According to the fourth embodiment, a travel schedule can readily becreated for the target moving object, which allow the target movingobject to travel in an efficient way even if a moving object other thanthe scheduling target moving object also uses the travel path network.

Fifth Embodiment

FIG. 20 illustrates an exemplary configuration of an operationscheduling system according to a fifth embodiment. The operationscheduling system includes a travel status output device 20 (secondoutput device) in addition to the same components as those of theoperation scheduling system in FIG. 1. The travel status output device20 obtains information including time-series networks corresponding torespective times generated by a time-series network generator 101, andoutputs the obtained information out of the operation scheduling system.

The time-series network information may be provided in a visible formthat can be displayed on the screen of a display device viewable tousers or workers. The display device may be installed on a wall in thefield to be viewed by a large number of users simultaneously. Thetime-series network information may be transmitted to an external devicesuch as user's terminal via wired or wireless communication.

The time-series network information may reflect the travel schedules ofall the moving objects that a route scheduler 100 processes or thetravel schedules of some of those moving objects (e.g., informationincluding time-series networks in the course of processing by the routescheduler 100).

Displaying time-series network information on a display device makes itpossible to warn workers to keep away from a travel path around the timewhen a moving object travels on the travel path. Users can readilyunderstand the travel schedule of each moving object by viewing thetime-series network information.

Sixth Embodiment

FIG. 21 is a block diagram of an operation scheduling system accordingto a sixth embodiment. The operation scheduling system includes a travelscheduler 31, an update position determiner 32 and a reschedulingdeterminer 33 in addition to the same components as those of theoperation scheduling system in FIG. 1. The rescheduling determiner 33determines whether travel schedules for moving objects created by aroute scheduler 100 and stored in a travel schedule storage 16 need tobe rescheduled. For example, the rescheduling determiner 33 determineswhether contention occurs between the moving objects while the travelschedules are executed. If contention occurs, the reschedulingdeterminer 33 determines that rescheduling is required. The reschedulingdeterminer 33 may determine that rescheduling is required if there is amoving object that cannot operate as scheduled (e.g., if there is amoving object that cannot arrive in time for the start of its task)while the travel schedules are executed. The rescheduling determiner 33may also determine that rescheduling is required if new tasks areassigned to moving objects.

The travel scheduler 31 recreates (updates) the travel schedules of themoving objects if the rescheduling determiner 33 determines thatrescheduling is required. In the travel schedules, portions of theroutes of the moving objects are updated, which the moving objects havenot traveled yet.

The update position determiner 32 determines positions of the movingobjects where the travel schedules of the moving objects are updated(update positions). In particular, portions of the routes of the movingobjects following the update positions are updated by the travelscheduler 31. If the moving objects can communicate with an operationmanagement apparatus 200 via a communicator 201 in real time, the updatepositions may be any suitable positions (e.g., the current positions ofthe moving objects, or positions at some later time to allow a marginfor calculation). If the moving objects cannot communicate via thecommunicator 201, the update positions may be positions where the movingobjects can communicate via communication devices 501. The updatepositions may be any nodes included in the travel path network. Thetravel scheduler 31 creates routing schedules for the moving objectswhich begin at the update points of the moving objects.

The travel scheduler 31 may not change portions of the routes of movingobjects following the update positions in the current travel schedules.The travel scheduler 31 may determine the routes of moving objects againusing the route scheduler 100. The travel scheduler 31 may determine theroutes of moving objects again in such way as to reduce the distancesthe moving objects travel in opposite directions on the same travel pathat the same time. The travel scheduler 31 recreate (updates) the travelschedule of each moving object by setting to each node included inportions of the route of the moving object following the update positiona timing at which the moving object travels through the node (at leastone of the departure time, arrival time and passage time). For example,timings at which the moving objects travel through nodes included in theroutes of the moving objects may be determined in such a manner as toprevent contention between the moving objects on travel paths. Timingsat which the moving objects travel through nodes may be determined onthe assumption that the moving objects travel at constant velocities.Timings at which the moving objects travel through nodes may bedetermined in any other suitable manners.

The travel scheduler 31 stores the updated travel schedules of themoving objects in the travel schedule storage 16. A director 14generates instructions for the moving objects based on the updatedtravel schedules. The director 14 provides the instructions based on theupdated travel schedules for the moving objects when the moving objectsare at the update points.

As described above, according to the present embodiment, if apossibility of contention arises in the routes of moving objects, routesand travel schedules that do not cause contention between the movingobjects can be recreated. For example, if the route scheduler 100decreases the weights of arcs as time passes, the possibility ofcontention may rise over time. Even in this case, according to thepresent embodiment, travel schedules that do not cause contentionbetween moving objects can be recreated.

Two or more of the first to sixth embodiments may be combined. In thiscase, the effects of all the combined embodiments can be achievedsimultaneously. For example, an operation scheduling system having aconfiguration shown in FIG. 22 can be obtained by combining the secondto fifth embodiments. For another example, an operation schedulingsystem having a configuration shown in FIG. 23 can be obtained bycombining the second to sixth embodiments.

(Hardware Configuration)

FIG. 24 illustrates a hardware configuration of the prediction apparatus(information processing device) 10 according to the present approach.The information processing device 10 according to the present approachis constructed of a computer apparatus 600. The computer apparatus 600is provided with a CPU 601, an input interface 602, a display device603, a communication device 604, a main storage 605 and an externalstorage device 606, which are mutually connected by a bus 607.

The CPU (central processing unit) 601 executes a computer program forimplementing the above-mentioned respective functional components of theinformation processing device 10 on the main storage 605. The CPU 601executes the computer program and thereby implements the respectivefunctional components.

The input interface 602 is a circuit for inputting operation signalsfrom the input device such as a keyboard, mouse, and touch panel or thelike into the information processing device 10. The input interface 602corresponds to an input device.

The display device 603 displays data or information outputted from theinformation processing device 10. The display device 603 is, forexample, an LCD (Liquid Crystal Display), a CRT (Cathode Ray Tube), anda PDP (plasma display), but the display device 603 is not limitedthereto. The data or information outputted from computer apparatus 600can be displayed by this display device 603. The display device 603corresponds to an output device.

The communication device 604 is a circuit for the information processingdevice 10 to communicate with the external device by wireless or wiredmeans. Information can be inputted from the external device via thecommunication device 604. The information inputted from the externaldevice can be stored in the DB. The input device 120 or the outputdevice 130 that carries out the communication function can beconstructed on the communication device 604.

The main storage 605 stores a program that implements processing of thepresent approach, data necessary to execute the program and datagenerated by executing the program. The program is developed andexecuted on the main storage 605. The main storage 605 may be, forexample, RAM, DRAM or SRAM, but it is not limited to this. The variousDBs and the storage in each approach may be constructed on the mainstorage 605.

The external storage device 606 stores the above-described program anddata necessary to execute the program, data generated by executing theprogram or the like. The program and data are read into the main storage605 during processing of the present approach. The external storagedevice 606 is, for example, a hard disk, an optical disk, a flash memoryor a magnetic tape, but it is not limited to this. The various DBs andthe storage in each approach may be constructed on the external storagedevice 606.

Note that the above-described program may be pre-installed in thecomputer apparatus 600 or may be stored in a storage medium such as aCD-ROM. The program may be uploaded on the Internet.

Note that the computer apparatus 600 may be provided with one or aplurality of processors 601, input interfaces 602, display devices 603,communication devices 604 and main storages 605, and peripheral devicessuch as a printer and a scanner may be connected thereto.

In addition, the information processing device 10 may be constructed ofthe single computer apparatus 600 or may be configured as a systemcomposed of a plurality of mutually connected computer apparatuses 600.

While certain embodiments have been described, these embodiments havebeen presented by way of example only, and are not intended to limit thescope of the inventions. Indeed, the novel embodiments described hereinmay be embodied in a variety of other forms; furthermore, variousomissions, substitutions and changes in the form of the embodimentsdescribed herein may be made without departing from the spirit of theinventions. The accompanying claims and their equivalents are intendedto cover such forms or modifications as would fall within the scope andspirit of the inventions.

1. An information processing apparatus comprising: a weight determinerconfigured to determine weights of a plurality of travel paths in atravel path network based on timings at which a first moving objecttravels on travel paths included in a first route among the plurality oftravel paths; and a route creator configured to create a second route onwhich a second moving object travels in the travel path network based onthe weights of the plurality of travel paths.
 2. The informationprocessing apparatus according to claim 1, wherein the weight determineris further configured to determine the weights of the plurality oftravel paths for a plurality of times based on travel paths on which thefirst moving object travels for the plurality of times among theplurality of travel paths, and the route creator is further configuredto create the second route based on the weights of the plurality oftravel paths for the plurality of times.
 3. The information processingapparatus according to claim 2, wherein the route creator is furtherconfigured to create the second route based on travel paths that arereachable by the second moving object for the plurality of times and theweights of the plurality of travel paths for the plurality of times. 4.The information processing apparatus according to claim 2, whereinlengths of the plurality of times are different.
 5. The informationprocessing apparatus according to claim 4, wherein a length of a latertime of the plurality of times is longer.
 6. The information processingapparatus according to claim 1, wherein the route creator is furtherconfigured to determine timings at which the second moving objecttravels travel paths which are included in the second route among theplurality of travel paths, and the weight determiner is furtherconfigured to update the weights of the plurality of travel paths basedon the second route and the determined timings.
 7. The informationprocessing apparatus according to claim 1, wherein structure of thetravel path network changes according to time, and the weight determineris further configured to change, according to time, the travel pathnetwork based on which the weights are determined.
 8. The informationprocessing apparatus according to claim 1, wherein structure of thetravel path network changes according to time, and the weight determineris further configured to change, according to the time, weights oftravel paths included in a changed portion of the travel path network.9. The information processing apparatus according to claim 8, whereinstructure of the travel path network changes according to time, and theinformation processing apparatus further comprises a first output deviceconfigured to output information including structure of the travel pathnetwork according to the time.
 10. The information processing apparatusaccording to claim 1, wherein a second output device is configured tooutput first information including travel paths on which the firstmoving object travels for the plurality of times among the plurality oftravel paths.
 11. The information processing apparatus according toclaim 2, wherein the weight determiner is further configured to updatethe weights of the plurality of travel paths for the plurality of timesbased on reservation information for the plurality of travel paths forthe plurality of times.
 12. The information processing apparatusaccording to claim 1, further comprising: a director configured togenerate instruction data for instructing the second moving object totravel on the second route; and a communicator configured to transmitthe instruction data.
 13. The information processing apparatus accordingto claim 1, wherein the second route starts at a departure point of thesecond moving object and ends at a arrival point of the second movingobject.
 14. An information processing apparatus for determining, in atravel path network including a plurality of travel paths, weights ofthe plurality of travel paths based on timings at which a first movingobject travels on the travel paths, the weights being used fordetermining travel paths on which a second moving object travels amongthe plurality of travel paths.
 15. An information processing apparatuscomprising: a weight determiner configured to update, in a travel pathnetwork including a plurality of travel paths having respective weights,at least one of the plurality of travel paths at varying time intervals;and a route creator configured to create a route on which a movingobject travels in the travel path network based on the weights of theplurality of travel paths.
 16. An information processing methodcomprising: determining weights of a plurality of travel paths in atravel path network based on timings at which a first moving objecttravels on travel paths included in a first route among the plurality oftravel paths; and creating a second route on which a second movingobject travels in the travel path network based on the weights of theplurality of travel paths.
 17. A non-transitory computer readable mediumhaving a computer program stored therein which causes a computer toperform processes comprising: determining weights of a plurality oftravel paths in a travel path network based on timings at which a firstmoving object travels on travel paths included in a first route amongthe plurality of travel paths; and creating a second route on which asecond moving object travels in the travel path network based on theweights of the plurality of travel paths.
 18. An information processingsystem comprising: a first moving object; a second moving object; and aninformation processing apparatus comprising a weight determinerconfigured to determine weights of a plurality of travel paths in atravel path network based on timings at which the first moving objecttravels on travel paths included in a first route among the plurality oftravel paths; and a route creator configured to create a second route onwhich the second moving object travels in the travel path network basedon the weights of the plurality of travel paths.